Experiments
Searchable full-text extractions: founding hypothesis, core claims, experimental setups, key results and statistics — pulled out of each paper as structure. Search a cell line, an assay or an entity (e.g. HUH7) and find every paper that worked with it. This corpus stands on its own: most entries carry no reproduction assessment (yet).
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Has reproduction · 74
SpaGene: A Deep Adversarial Framework for Spatial Gene Imputation.
PMID 42146899 · PMC13176606 · Computational and structural biotechnology journal · 2026 · 8 claims · 6 setups
SpaGene improves average PCC and SSIM and reduces RMSE compared to 6 baseline methods (SpaGE, gimVI, Tangram, VISTA, spRefine, stDiff) across 8 diverse ST-SC dataset pairs under gene-holdout evaluation.
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Machine-learning approaches for classifying haplogroup from Y chromosome STR data.
PMID 18551166 · PMC2396484 · PLoS computational biology · 2008 · 8 claims · 5 setups
Y-STR allelic variability is partitioned more by differences among haplogroups than by differences among populations, suggesting Y-STRs carry haplogroup information
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Cancer-specific high-throughput annotation of somatic mutations: computational prediction of driver missense mutations.
PMID 19654296 · PMC2763410 · Cancer research · 2009 · 7 claims · 7 setups
CHASM, a Random Forest-based computational method, was developed to identify and prioritize missense mutations likely to be functional drivers of tumor cell proliferation.
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GoMiner: a resource for biological interpretation of genomic and proteomic data.
PMID 12702209 · PMC154579 · Genome biology · 2003 · 8 claims · 4 setups
GoMiner organizes 'interesting' gene lists (e.g., differentially expressed genes) into the Gene Ontology hierarchy for biological interpretation, displaying results as both a tree and a directed acyclic graph (DAG).
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Has reproduction · 81
Enabling Single-Cell Drug Response Annotations from Bulk RNA-Seq Using SCAD.
PMID 36762572 · PMC10104628 · Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2023 · 7 claims · 7 setups
SCAD, a transfer learning framework integrating adversarial discriminative domain adaptation (ADDA), can infer single-cell drug sensitivities by transferring knowledge from bulk RNA-seq pharmacogenomic data (GDSC) to scRNA-seq target domains